Lipidomics, the large-scale study of the pathways and networks of cellular lipids, is an emerging and rapidly expanding research field. Through the analyses of brain lipids using shotgun lipidomics, a technology recently developed by the PI, we have shown that a substantial mass loss of sulfatide (a class of specialized myelin sphingolipids) and a significant mass increase in ceramide (a class of sphingolipid metabolites associated with cell death) are present in individuals at the earliest clinically-recognizable stage of Alzheimer's disease (i.e., very mild AD). Sulfatide loss and ceramide elevation represent early events in AD pathogenesis and may contribute to neurodegeneration, synapse loss, and the development of AD pathology. However, the cause(s) leading to these changes still remain unknown. Moreover, it is unclear whether alterations in the mass levels of other sphingolipid classes also occur in very mild AD, which pathways are changed leading to these alterations, and whether these lipid alterations are potential biomarkers for the early diagnosis of AD. To identify the cause(s) of sulfatide loss and ceramide increase in AD and to address the above questions, we will further develop shotgun lipidomics to analyze all lipid classes of interest, specifically many minor sphingolipid classes. A bioinformatics approach will be developed to yield automated, high-throughput processing of complex lipidomics data, to identify the altered lipid molecular species induced by a disease state, and to construct a lipid metabolic network map. The structure of the developed platform should be suitable to identify altered pathways of lipid metabolism induced by any disease state. However, we will focus our proposed studies on the identification of the biochemical mechanism(s) underlying the altered pathways of the sphingolipidome networks present in very mild AD and the discovery of potential lipid biomarkers for the early diagnosis of AD through determination of the altered lipid profiles of brain tissue and cerebrospinal fluid from subjects with very mild AD using the developed platform. Collectively, in this application, we will further develop shotgun lipidomics and an integrated bioinformatics program and will apply this developed platform for AD studies. The obtained results will reveal the biochemical mechanisms underlying sulfatide loss in AD, identify novel lipid biomarkers for the early diagnosis of AD, and provide insight into AD pathogenesis.